[exekias]

For migrations altering columns (for instance adding a constraint), data gets upgraded/downgraded between old and new versions trough the up/down functions. These are defined by the migration. They work like this:

- For rows inserted/updated through the old version of the schema, the up function gets executed, copying the resulting value into the new column - For rows inserted/updated through the new version, the down function gets executed, copying the resulting value into the old column

For instance, you can test that up function works before releasing the new app relying on it, just by checking that the values present in the new schema are correct.

[jedberg]

What happens if you write into the old table with data that violates the constraint the new schema adds? Does the up function fail?

[surjection]

An example would make this more concrete.

This migration[0] adds a CHECK constraint to a column.

When the migration is started, a new column with the constraint is created and values from the old column are backfilled using the 'up' SQL from the migration. The 'up' SQL rewrites values that don't meet the constraint so that they do.

The same 'up' SQL is used 'on the fly' as data is written to the old schema by applications - the 'up' SQL is used (as part of a trigger) to copy data into the new column, rewriting as necessary to ensure the constraint on the new column is met.

As the sibling comment makes clear, it is currently the migration author's responsibility to ensure that the 'up' SQL really does rewrite values so that they meet the constraint.

[0] - https://github.com/xataio/pgroll/blob/main/examples/22_add_c...

[exekias]

Yes, this is the case as of today. It's important to get the up/down functions right.

The good thing is that this will probably be detected during the start phase, as data would fail to be backfilled.

We are thinking of ideas to improve this in the longer term, for example: * Having a dry-run mode where you check that the data present in the DB will stay valid after applying the up function * Optionally allow for this to happen, but "quarantine" the affected rows so they are no longer available in the new schema.